Vignette of rGMAP package
rGMAP version 1.4
Updated on 2019-02-16
Contents
1 Introduction
- rGMAP is an R package for implementing GMAP algorithm for detecting topologically associating domains (TADs) and sub-domains (sub-TADs)
- The detailed of the algorithm can be found in Yu, W., He, B., & Tan, K. (2017). Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion test. Nature Communications, 8, 535
2 Updates
- The inputs of rGMAP function support both data frame/data table and tab/space delimited text file for both hic_obj and index_obj, and are consitent with the inputs of plotdom function
- n by n matrix of hic_obj is still supported, where n is the total number of bins of a hic contact map for a single chromosome
3 Note
- The index file index_obj was required in multiple chromosome mode
- If the input hic_obj is just from a sigle chromosome and no index_file was provided: the first two columns should be the i_th, j_th bin of the chromosome if hic_obj is in 3-column format (i j count)
4 Installation
4.1 Install from Github
library(devtools)
install_github('wbaopaul/rGMAP')
4.2 Install from source codes
install.packages('path to rGMAP_1.4.tar.gz', repos = NULL, type = 'source')
5 Examples
5.1 Work on an published Hi-C data
Data from Rao et al., Cell 2014, A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping
KR normalized Hi-C data for IMR90 cell line, on chr15 with resolution 10kb
library(rGMAP)
hic_rao_IMR90_chr15
#> n1 n2 count
#> 1: 2001 2001 1594.4993397
#> 2: 2001 2002 173.5189748
#> 3: 2002 2002 2012.2132432
#> 4: 2001 2003 7.1718521
#> 5: 2002 2003 6.0486110
#> ---
#> 3553174: 10237 10250 0.8934246
#> 3553175: 9729 10251 1.0049196
#> 3553176: 9861 10251 1.9337094
#> 3553177: 10005 10251 0.8993636
#> 3553178: 10237 10251 0.8934246
res = rGMAP(hic_rao_IMR90_chr15, index_obj = NULL, resl = 10 * 1000, dom_order = 2)
names(res)
#> [1] "tads" "hierTads" "params"
#quickly visualize some hierarchical domains
pp = plotdom(hic_rao_IMR90_chr15, index_obj = NULL, res$hierTads, chr0 = NULL, 5950, 6900, 30, 10000)
pp$p2
5.2 Compatible with HiC-Pro output matrix and index file
- The format of the index file (10kb for example):
chr1 0 10000 1
chr1 10000 20000 2
chr1 20000 30000 3
chr1 30000 40000 4
......
- The format of the hic_mat data:
10 127 10.372577
10 188 4.161271
10 281 36.072713
17 5822 2.418056
......
5.3 Work on an simulated example
set.seed(1)
simu_res = data_simu('poisson-dist-hier')
true_domains = simu_res$hierTads
simu_mat = simu_res$hic_mat
predicted_domains = rGMAP(simu_mat, resl = 1)$hierTads
pp = plotdom(simu_mat, NULL, predicted_domains, NULL, 1, 1000, 20, resl = 1)
pp$p2
#true_domains
#predicted_domains
6 Session Information
devtools::session_info()
#> ─ Session info ────────────────────────────────────────────────────────────
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#> tz Asia/Shanghai
#> date 2019-02-16
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